There is an increasing demand for energy sources throughout the world along with the global urbanization and modernization courses, especially the rapid development of the overpopulated developing countries. Also numerous energy sources result from the combustion of minerals, and the extensive use of the energy sources will influence the environment in that the emission of greenhouse gas will result in global warming. Thus the efficient use and conservation of the energy sources is becoming an issue of great importance.
At present there are roughly two methods for energy saving. One method is to produce more efficient devices in using energy sources, and the other method is to reduce the consumption amount of energy sources through the persistent participation of device owners. As stated in the documents, the latter method may appear more feasible and can be accepted more easily due to a cost thereof far below that of the former method.
In order to enable device owners to participate in a persistent energy-saving process, an important issue is the knowledge of how people use their devices to thereby get rid of their bad routines of using energy sources or assist them in changing their own routines of using energy sources.
Thus the status of a power consumption device is detected, for example, the time for which the power consumption device is in an on/off or standby status, the time for which the power consumption device is in use, etc., and this is a technology of great importance to energy saving.
As illustrated in FIG. 1, there is currently the following scheme for detecting the statuses of power consumption devices:
In a first operation, a measurement value of a power electricity meter is stored in a power measurement storing unit, and other collected perceptive data, e.g., temperature, humidity, etc., and information of the devices is stored in an additional data storing unit;
In a second operation, a device status estimating unit estimates the statuses of the respective devices using the stored information above, assigns a probability value to the estimated status of each device and stores an estimation result in a device probable status and related probability storing unit; and
In a third operation, a status acceptance decider compares the total power calculated from the status estimation result above with the total measured power. If the difference between the calculated total power and the total measured power is below a preset power threshold, then the status estimation result above is accepted and stores in a device status storing unit; otherwise, a status probability re-estimator defines the statuses of some devices according to the probability values obtained in the second operation and the decision condition of this operation and then the flow returns to the second operation where the device status estimating unit re-estimates the statuses of the devices according to the definition condition, thus resulting in a feedback loop.
An example will be described below:
Power measurement data stored in the power measurement storing unit is assumed as follows:
L = { “Time: 2011-11-1 12:34:23, Electricity Meter No. 1, Voltage: 220 V, Current: 23 mA” ,“Time: 2011-11-1 12:34:23, Electricity Meter No. 2, Voltage: 220V, Current: 30 mA” ,“Time: 2011-11-1 12:34:26, Electricity Meter No. 1, Voltage: 220V, m Current: 10 mA” ,... ...}
Additional data stored in the additional data storing unit is assumed as follows:
A = {“Device No.: 1, 30w/h, Use Mode: Always from 6p.m to 9p.m”, “Device No.: 2, 10w/h, Use Mode: Always from 6a.m to 7a.m”, “Device No.: 3, 25w/h, Use Mode: Always from 6a.m to 7a.m”, “Temperature: 23.2 at 2011-11-1 12:34:23”, “Humidity: 30% at 2011-11-1 12:34:23”... ...}
Whether the devices are in an on or off status and corresponding probability values may be inferred from the information above, particularly as follows:
O1= {Device No. 1: Off with 20%,Device No. 2: Off with 40%,Device No. 3: On with 80%, ...}
The total power is estimated from O1 and A as 30×0+10×0+25×1=25w. Given the total measured power of 35w and a given threshold of 5w, the estimation result above can not be accepted due to 35w−25w=10>5w.
The status probability re-estimator defines the device No. 3 in an on status according to the probability values (because the device No. 3 is in an on status with the probability of 80%) and notifies the device status estimating unit of the definition result, and the device status estimating unit re-estimates the statuses of the devices as the following new estimation result:
O2= {Device No. 1: Off with 20%,Device No. 2: Off with 90%,Device No. 3: On with 80%, ...}
The status acceptance decider compares the total power estimated from the result above of O2 with the total measured power. The estimated total power is 25+10=35w, and the total measured power is also 35w, so the difference between them is zero and below the given threshold. Thus the result can be accepted and outputted as:
O={Device No. 1: Off, Device No. 2: On, Device No. 3: On}.
The foregoing scheme for detecting the statuses of devices has to be performed inefficiently with a number of feedback loops. A problem currently desirable to be addressed is how to improve the efficiency of detecting the statuses of devices.